Methods of suppressing ringing artifact of decompressed images

ABSTRACT

A suppression method that provides adaptive (i.e., selective) processing of an input picture to generate an enhanced output picture with ringing-like areas of the input picture suppressed. For each such window in the input picture, if the window is detected as around a ringing-like area in the picture, then the output pixel for the position of the window comprises the low-pass filtered (i.e., smoothed) pixel in the input picture. However, if the window is not detected as around a ringing-like area (i.e., the window is around a non-ringing-like area) then the output pixel for the position of the window comprises essentially the unchanged window in the input picture. As a result no blurring is introduced into the input picture in areas where ringing-like patterns are not detected. Therefore, the output picture includes portions of the input picture in which ringing-like patterns were not detected, and portions of the input picture with suppressed ringing-like patterns where detected. The output picture is an enhanced version of the input picture with suppressed (i.e., smoothed) ringing-like patterns.

FIELD OF THE INVENTION

[0001] The present invention relates generally to video processing, andmore particularly to video image compression.

BACKGROUND OF THE INVENTION

[0002] The development of modern digital video technology has enhancedthe video quality for consumer electronics such as in DVD players anddigital TV (DTV) systems, as compared to analog TV systems. However,significant video enhancement shortcomings remain in digital videosystems such as DTV systems, including contrast enhancement, brightnessenhancement and detail enhancement.

[0003] Post processing for decompressed pictures plays an important rolein the quality of any digital video system depending on compressiontechnology. This is because artifacts inherently arise as a result ofdata quantization in data compression. Examples include blockingartifacts, ringing artifacts, mosquito noise, etc. When a digital imageor video has been compressed to a low bit rate, such artifacts areespecially annoying.

[0004] Conventionally, a low-pass-filter has been used to remove theringing artifacts from the digital picture. However, the low-pass-filteralso removes the picture details which introduces blurring artifacts.There is, therefore, a need for a method of suppressing ringingartifacts that commonly arise in decompressed pictures.

BRIEF SUMMARY OF THE INVENTION

[0005] The present invention addresses the above shortcomings. In oneembodiment, the present invention provides a systematic way of detectingringing-like areas in a picture by examining local statistics. Thisallows adaptive suppression of ringing artifacts without introducingblurring to the areas where no ringing artifacts are detected.

[0006] A suppression method that provides adaptive (i.e., selective)processing of an input picture to generate an enhanced output picturewith ringing-like areas of the input picture suppressed. Subsets of theinput picture are analyzed as one or more windows. For each such windowin the input picture, if the window is around a ringing-like area in thepicture, then the output picture comprises the low-pass filtered (i.e.,smoothed) window in the input picture. However, if the window is notaround a ringing-like area (i.e., the window is around anon-ringing-like area) then the output picture comprises essentially theunchanged window in the input picture. As a result no blurring isintroduced into the input picture in areas where ringing-like patternsare not detected. Therefore, the output picture includes portions of theinput picture in which ringing-like patterns were not detected, andportions of the input picture with suppressed ringing-like patternswhere detected. The output picture is an enhanced version of the inputpicture with suppressed (i.e., smoothed) ringing-like patterns.

[0007] In another embodiment, the present invention further provides adevice that adaptively reduces ringing artifacts in an input imageincluding pixels of image information. In one example, such a devicereduces ringing artifacts comprises: a ringing-artifact detector thatdetects areas of ringing artifacts in a pixel window based on the pixelinformation, the pixel window including a set of pixels from the inputimage pixels; an image processor that processes window pixels togenerate pixels with reduced ringing artifacts; and a combiner thatselects the processed pixels with reduced ringing artifacts in thedetected ringing-artifact areas, and generates an output imagecomprising: (i) the selected processed pixels with reduced ringingartifacts, and (ii) the remaining window pixels.

BRIEF DESCRIPTIONS OF THE DRAWINGS

[0008] These and other features, aspects and advantages of the presentinvention will become understood with reference to the followingdescription, appended claims and accompanying figures where:

[0009]FIG. 1 shows an example window in a digital picture that isprocessed using an embodiment of an adaptive suppression methodaccording to the present invention;

[0010]FIG. 2 shows a flowchart of the steps of an embodiment of anadaptive suppression method according to the present invention;

[0011]FIG. 3 shows an example curve representing an example relationshipbetween local variances σ(y,x) in a signal detection function β(y,x);and

[0012]FIG. 4 shows a block diagram of an example architecture of anadaptive suppression device according to the present invention.

DETAILED DESCRIPTION OF THE INVENTION

[0013] Overview

[0014] As noted above, in one embodiment, the present invention providesa method of detecting ringing-like areas in a picture by examining localstatistics in the picture. This allows adaptive reduction (e.g.,suppression) of ringing artifacts in decompressed pictures, withoutintroducing blurring to the areas where no ringing artifacts arepresent, according to the present invention. Referring to FIG. 1, in oneexample, the set {I} denotes a decompressed picture (field or frame) 10,and I(y,x) denotes a gradation value of the x^(th) pixel 12 of they^(th) line of the picture 10.

[0015]FIG. 2 shows a flowchart of the steps of an example suppressionmethod according to the present invention. The suppression methodincludes the steps of:

[0016] Computing local variance/deviation σ(y,x) for each pixel 12 inthe image 10 based on neighboring pixels in the NXM window 14 (step 20);

[0017] Using the local variances σ(y,x) in a signal detection functionβ(y,x) to detect if the window 14 is in a noisy area (small localdeviation) or in a good signal area (large local deviation), in theinput picture 10 (step 22);

[0018] Detecting ringing-like patterns in the window 14 using aringing-like pattern detection function g(y,x) (step 24);

[0019] Using detection of noisy/signal area and detection ofringing-like-patterns in a ringing-like pattern area function γ(y,x) todetermine if the window 14 is around ringing-like pattern area in thepicture 10 (step 26)

[0020] Performing low pass filtering on a copy of the input picture 10(step 28); and

[0021] Selectively combining portions of {I} with portions ofI_(LPF)(y,x) based on detected ringing-like pattern areas, to generateenhanced signal J(y, x) where ringing-like areas are essentiallysuppressed (step 30).

[0022] Such a method provides adaptive (i.e., selective) processing ofthe input picture 10 to generate an enhanced output picture withringing-like areas of the input picture 10 suppressed. As such, in theabove example, for each input pixel I_(n)(y,x). Based on such N×Mneighbor pixel window 14, if the window 14 is around a ringing-like areain the picture 10, then the output pixel J(y, x) comprises the low-passfiltered (i.e., smoothed) pixel of the input picture. However, if thewindow 14 is not around a ringing-like area (i.e., the window is arounda non-ringing-like area) then the output pixel J(y, x) comprisesessentially the unchanged pixel of the input picture which is J(y, x).As a result no blurring (due to smoothing) is introduced into the inputpicture in areas where ringing-like patterns are not detected.Therefore, the output picture comprises portions of the input picture inwhich ringing-like patterns were not detected, and portions of the inputpicture with low pass filtering where ringing-like patterns weredetected. Note that this changes from pixel to pixel. The output pictureis an enhanced version of the input picture with suppressed (i.e.,smoothed) ringing-like patterns.

[0023] Example Implementation

[0024] In one example implementation described hereinbelow, I_(LPF)(y,x)denotes the gradation value of the x^(th) pixel of the y^(th) line ofthe picture {I} after low-pass-filtering. A local deviation σ(y,x) forI(y,x) in the picture {I} is computed based on the local/neighboringsamples (pixels) of I(y,x). This can be performed using a windowcentered at (y,x) and computing the variance of the samples in thewindow. Although any arbitrary window shape can be used, an N×Mrectangular window is used in the description herein for explanationpurposes.

[0025] The deviation value σ(y,x) can be computed as: $\begin{matrix}{{\sigma \left( {y,x} \right)} = \sqrt{\frac{\sum\limits_{i = 1}^{N}\quad {\sum\limits_{j = 1}^{M}\left( {w_{i,j} - {m\left( {y,x} \right)}} \right)^{2}}}{N \cdot M}}} & (1)\end{matrix}$

[0026] where w_(i,j) is the (i,j)^(th) element of the N×M rectangularwindow, and m(y,x) is the mean of the samples in the N×M rectangularwindow, wherein:${m\left( {y,x} \right)} = {\frac{\sum\limits_{i = 1}^{N}\quad {\sum\limits_{j = 1}^{M}w_{i,j}}}{N \cdot M}.}$

[0027] Because the expression in relation (1) can be expensive tocompute, alternatively the following relation can be used to determinethe local deviation, wherein: $\begin{matrix}{{\sigma \left( {y,x} \right)} = {\frac{\sum\limits_{i = 1}^{N}\quad {\sum\limits_{j = 1}^{M}{{w_{i,j} - {m\left( {y,x} \right)}}}}}{N \cdot M}.}} & (2)\end{matrix}$

[0028] Further, the denominator N·M in relation (2) is a constant, oncethe dimensions of the window have been determined. As such, thefollowing relation can be used to determine a relative quantity of thelocal deviation as: $\begin{matrix}{{\sigma \left( {y,x} \right)} = {\sum\limits_{i = 1}^{N}\quad {\sum\limits_{j = 1}^{M}\quad {{{w_{i,j} - {m\left( {y,x} \right)}}}.}}}} & (3)\end{matrix}$

[0029] A computation according to relation (3) is simpler in terms of ahardware implementation than (1) or (2).

[0030] Detecting Noisy and Good-Signal Image Areas

[0031] Based on the local deviation σ(y,x), a signal detection functionβ(y,x) based on σ(y,x) is selected, wherein the signal detectionfunction β(y,x) satisfies the following three constraints:

[0032] As σ(y,x) increases, β(y,x) approaches 1,

[0033] As σ(y,x) decreases to 0, β(y,x) approaches 0, and

[0034] β(y,x) monotonically increases as σ(y,x) increases.

[0035] Other signal detection functions which satisfy the above threeconstraints can also be utilized.

[0036] As described further below, the role of the signal detectionfunction β(y,x) is to detect whether the widow is located in a noisyarea (i.e., small local deviation), in a signal area (i.e., large localdeviation) or between. In this example, the value of β(y,x) is boundedas 0≦β(y,x)≦1. In general, when β(y,x) is close to zero, it implies thewindow is substantially in a noisy area, and when β(y,x) is close toone, it implies that the window is substantially in a signal area (forsimplicity, it is assumed that the noise level is smaller than thesignal level).

[0037] One example of the signal detection signal β(y,x) can be:$\begin{matrix}{{\beta \left( {y,x} \right)} = \left\{ \begin{matrix}{0,} & {{\sigma \left( {y,x} \right)} \leq t_{1}} \\\frac{{\sigma \left( {y,x} \right)} - t_{1}}{t_{2} - t_{1}} & {t_{1} \leq {\sigma \left( {y,x} \right)} \leq t_{2}} \\{1,} & {{\sigma \left( {y,x} \right)} \geq t_{2}}\end{matrix} \right.} & (5)\end{matrix}$

[0038] wherein t₁ and t₂ are some pre-determined constants. As shown bythe example curve 31 in FIG. 3, depending on the values of t₁and t₂, thecharacteristics of β(y,x) can be defined in association with the valueof σ(y,x). The ranges for t₁and t₂ are dependent on application.

[0039] Detecting Ringing-Like Patterns

[0040] In detecting a ringing-like pattern in the window, in oneexample, a ringing like area is recognized as a weak (small) edge area.The weak edge area is indicated by a gradation level difference betweena pixel and its neighboring pixels, that is within a selected threshold.In one example, a relatively small gradation level difference indicatesthat there might be weak (small) edge at the pixel position. A largegradation level difference implies that there might be a strong edge atthe pixel position. In real images, ringing does not exhibit a strongedge. Therefore, to detect a ringing-like pattern in the window, apattern detection function g(y,x) is utilized, wherein g(y,x) includesthe components g_(x)(y, x) and g_(y)(y, x), such that: $\begin{matrix}{{g_{x}\left( {y,x} \right)} = \frac{\Delta_{x}^{\min}}{\Delta_{x}^{\max}}} & (6)\end{matrix}$

[0041] where:

Δ_(x) ^(max)=max(|I(y,x−1)−I(y,x)|,|I(y,x+1)−I(y,x)|)

Δ_(x) ^(min)=min(|I(y,x−1)−I(y,x)|,|I(y,x+1)−I(y,x)|),

and $\begin{matrix}{{g_{y}\left( {y,x} \right)} = \frac{\Delta_{y}^{\min}}{\Delta_{y}^{\max}}} & (7)\end{matrix}$

[0042] where:

Δ_(y) ^(max)=max(|I(y+1,x)−I(y,x)|,|I(y−1,x)−I(y,x)|)

Δ_(y) ^(min)=min(|I(y+1,x)−I(y,x)|,|I(y−1,x)−I(y,x)|).

[0043] The component g_(x) (y, x) indicates ringing pattern-likefeatures in the horizontal direction in the window and the componentg_(y)(y, x) indicates ringing pattern-like features in the verticaldirection in the window. As such, the ringing-like pattern detectionfunction g(y,x) can be represented as:

g(y,x)=max(g _(x)(y,x),g _(y)(y,x))  (8)

[0044] where 0≦g(y,x)≦1.

[0045] For a given pixel I(y, x) the larger the gradation leveldifference between that pixel and its neighboring pixels, then the lowerthe ringing effect (i.e., g(y,x) decreases). When g(y,x) is close tozero, it implies a substantially non-ringing-like pattern, and wheng(y,x) is close to one, it implies a substantially ringing-like pattern.

[0046] Detecting Ringing-Like Areas

[0047] A combination of the signal detection function β(y,x) and theringing-like pattern detection function g(y,x), provides a ringing-likearea detection function γ(y,x) which satisfies the constraints in Table1 below: g(y, x) γ(y, x) 0 → 1 β(y, x) 0 0 . . . 1 ← ⋮

⋱

⋮

1 0 . . . 0

[0048] The arrows in Table 1 indicate a corresponding value changingfrom e.g., 0 to 1.

[0049] One example of the function γ(y,x) satisfying said constraintscan be:

γ(y,x)=(1−β(y,x))·g(y,x).  (9)

[0050] In one example, when γ(y,x)=1, it implies that the window islocated around a ringing-like pattern area, whereas when γ(y,x)=0, itimplies that the window is located around a non-ringing-like patternarea.

[0051] Generating Enhanced Output Image

[0052] Based on the ringing-like area detection function γ(y,x), anenhanced output J(y, x) is provided as:

J(y,x)=(1−γ(y,x))·I(y,x)+γ(y,x)·I _(LPF)(y,x)  (10)

[0053] wherein J(y, x) combines the original sample values I(y, x) andthe low-pass-filtered values I_(LPF)(y, x) depending on the degree ofringing-like value γ(y,x).

[0054] If a ringing-like area is detected (e.g., γ(y,x)=1), then:

J(y,x)=I _(LPF)(y,x)

[0055] which implies a smoothed output.

[0056] If a non-ringing-like area is detected (e.g., γ(y,x)=0), then:

J(y,x)=I(y,x)

[0057] which implies that no change is made and thus no blurring isintroduced.

[0058] Relation (10) above represents a point-to-point process, whereinthe value of γ(y,x) is estimated point-to-point (or, pixel-to-pixel).Hence, relation (10) provides an adaptive de-ringing method according toan embodiment of the present invention.

[0059] Although in the preferred embodiment described above, both thesignal detection function β(y,x) and the pattern-like detection functiong(y,x), are used in relations (9) and (10) above, in other embodimentsof the present invention, the pattern-like detection function g(y,x) canbe used independent of the signal detection function β(y,x). As such, inan alternative example, relation (10) above for generating the outputpicture J(y, x) can modified to be:

J(y,x)=(1−g(y,x))·I(y,x)+g(y,x)·I _(LPF)(y,x)  (10a)

[0060] Adaptive Suppression Device

[0061]FIG. 4 shows a block diagram of an example architecture of anembodiment of an adaptive suppression device 40 according to the presentinvention, implementing the above method. The device 40 includes: alow-pass filter (LPF) block 42; a local variance compute block 44 thatcomputes the local deviation σ(y,x) for a pixel in a window based onneighboring pixels; signal detection function block 46 that uses thelocal variances σ(y,x) to detect location of the window in relation tonoisy and signal areas in the input picture; a ringing-like detectionfunction block 48 that detects ringing-like patterns using the functionβ(y,x); a ringing-like area detection block 50 that uses detection ofnoisy/signal area and detection of ringing-like-patterns in theringing-like pattern area function γ(y,x) to determine if window isaround ringing-like pattern area in the picture; and a combiner thatselectively combines portions of {I} with portions of I_(LPF)(y,x) basedon detected ringing-like pattern areas (as described), to generateenhanced output signal J(y, x) representing an output picture in whichringing-like areas are essentially suppressed .

[0062] The example suppression device in FIG. 4 can be implemented inmany ways known to those skilled in the art, such as for example, asprogram instructions for execution by a processor, as logic circuitssuch as ASIC, etc. For example, instead of low pass filtering, othermethods of suppressing ringing like artifacts in the input picture canbe used according to the present invention. Further, other methods fordetecting other artifacts, and suppression of such artifacts can also beutilized according to the present invention. As such, while thisinvention is susceptible of embodiments in many different forms, thereare shown in the drawings and described herein, preferred embodiments ofthe invention with the understanding that the present disclosure is tobe considered as an exemplification of the principles of the inventionand is not intended to limit the broad aspects of the invention to theembodiments illustrated. Therefore, the spirit and scope of the appendedclaims should not be limited to the description of the preferredversions contained herein.

What is claimed is:
 1. A method for adaptive reduction of ringingartifacts in an input image including pixels of image information,comprising the steps of: (a) selecting a pixel window including a set ofpixels from the input image pixels; (b) detecting areas of ringingartifacts in the pixel window based on the pixel information; (c)processing the pixels in the detected areas to reduce the detectedringing artifacts in those areas; and (d) generating an enhanced outputimage including the processed pixels with reduced ringing artifacts. 2.The method of claim 1, wherein in step (b) detecting the areas ofringing artifacts includes the steps of: detecting areas of ringingartifacts in the pixel window as a function of gradation leveldifferences between one or more pixels therein.
 3. The method of claim1, wherein in step (b) detecting the areas of ringing artifacts includesthe steps of: for a pixel in the window, determining the gradation leveldifference between that pixel and that of neighboring pixels; anddetecting if the gradation level difference is within a selectedthreshold, indicating ringing-like artifacts proximate the pixelposition in the window.
 4. The method of claim 1, wherein in step (c)processing said pixels includes the steps of performing low passfiltering of the pixels to reduce the ringing artifacts.
 5. The methodof claim 1, wherein in step (c) processing said pixels includes thesteps of performing smoothing on the pixels to reduce the ringingartifacts.
 6. The method of claim 1, wherein in step (d) generating anenhanced output image further includes the steps of: generating anenhanced output image comprising: (i) the processed window pixels withreduced ringing artifacts, and (ii) the remaining window pixels.
 7. Themethod of claim 1 wherein the input image comprises a decompressedimage.
 8. A method for adaptive reduction of ringing artifacts in aninput image including pixels of image information, comprising the stepsof: (a) selecting a pixel window including a set of pixels from theinput image pixels; (b) detecting areas of ringing artifacts in thepixel window based on the pixel information; (c) processing the pixelsin the window to generate processed pixels including pixels with reducedringing artifacts; (d) selecting pixels with reduced ringing artifactsfrom the processed pixels, based on the detected ringing artifact areas;and (e) generating an enhanced output image comprising: (i) the selectedpixels, and (ii) the remaining window pixels.
 9. The method of claim 8,wherein in step (b) detecting the areas of ringing artifacts includesthe steps of: detecting areas of ringing artifacts in the pixel windowas a function of gradation level differences between one or more pixelstherein.
 10. The method of claim 8, wherein in step (b) detecting theareas of ringing artifacts includes the steps of: for a pixel in thewindow, determining the gradation level difference between that pixeland that of neighboring pixels; and detecting if the gradation leveldifference is within a selected threshold, indicating ringing-likeartifacts proximate the pixel position in the window.
 11. The method ofclaim 8, wherein in step (c) processing said pixels includes the stepsof performing low pass filtering of the pixels to reduce ringingartifacts.
 12. The method of claim 8, wherein in step (c) processingsaid pixels includes the steps of performing smoothing on the pixels toreduce ringing artifacts.
 13. The method of claim 8 wherein the inputimage comprises a decompressed image.
 14. A method for adaptivereduction of ringing artifacts in an input image including pixels ofimage information, comprising the steps of: (a) selecting a pixel windowincluding a set of pixels from the input image pixels; (b) detectingareas of ringing artifacts in the pixel window based on the pixelinformation; (c) determining local variance of each pixel in the windowwith respect to neighboring pixels; (d) based on the local variances,detecting if the location of the window is proximate a noisy area in theinput image; (e) processing the window pixels to generate processedpixels including pixels with reduced ringing artifacts; (f) selectingpixels with reduced ringing artifacts from the processed pixels, basedon the detected ringing artifact areas and the detected window locationinformation; and (g) generating an enhanced output image comprising: (i)the selected pixels, and (ii) the remaining window pixels.
 15. Themethod of claim 14, wherein in step (b) detecting the areas of ringingartifacts includes the steps of: detecting areas of ringing artifacts inthe pixel window as a function of gradation level differences betweenone or more pixels therein.
 16. The method of claim 14, wherein in step(b) detecting the areas of ringing artifacts includes the steps of: fora pixel in the window, determining the gradation level differencebetween that pixel and that of neighboring pixels; and detecting if thegradation level difference is within a selected threshold, indicatingringing-like artifacts proximate the pixel position in the window. 17.The method of claim 14, wherein in step (e) processing said pixelsincludes the steps of performing low pass filtering of the pixels toreduce ringing artifacts.
 18. The method of claim 14, wherein in step(e) processing said pixels includes the steps of performing smoothing onthe pixels to reduce ringing artifacts.
 19. The method of claim 14wherein the input image comprises a decompressed image.
 20. The methodof claim 14, wherein in step (f) selecting pixels with reduced ringingartifacts from the processed pixels, further includes the steps of: (f)selecting pixels with reduced ringing artifacts from the processedpixels in the detected ringing artifact areas, based on the windowlocation information.
 21. The method of claim 14, wherein in step (f)selecting pixels with reduced ringing artifacts from the processedpixels, further includes the steps of: (f) selecting pixels with reducedringing artifacts from the processed pixels in the detected ringingartifact areas, substantially in noisy picture locations.
 22. A devicethat adaptively reduces ringing artifacts in an input image includingpixels of image information, comprising: a ringing-artifact detectorthat detects areas of ringing artifacts in a pixel window based on thepixel information, the pixel window including a set of pixels from theinput image pixels; an image processor that processes window pixels togenerate pixels with reduced ringing artifacts; and a combiner thatselects the processed pixels with reduced ringing artifacts in thedetected ringing-artifact areas, and generates an output imagecomprising: (i) the selected processed pixels with reduced ringingartifacts, and (ii) the remaining window pixels.
 23. The device of claim22, wherein the ringing-artifact detector detects the areas of ringingin the pixel window as a function of gradation level differences betweenone or more pixels therein.
 24. The device of claim 22, wherein theringing-artifact detector determines the gradation level differencebetween a pixel and that of neighboring pixels, and detects if thegradation level difference is within a selected threshold, indicatingringing-like artifacts proximate that pixel position in the window. 25.The device of claim 22, wherein the image processor includes a low passfilter that reduces ringing artifacts.
 26. The device of claim 22,wherein the image processor includes a smoother that reduce ringingartifacts.
 27. The device of claim 22, further comprising: a variancedetector that determines local variance of each pixel in the window withrespect to neighboring pixels; a signal detector that based on the localvariances, detects if the location of the window is proximate a noisyarea in the input image; such that the combiner further selects pixelswith reduced ringing artifacts from the processed pixels, based on thedetected ringing artifact areas and the detected window locationinformation, and generates that enhanced output image comprising: (i)the selected pixels, and (ii) the remaining window pixels.
 28. Thedevice of claim 27, wherein the combiner pixels with reduced ringingartifacts from the processed pixels in the detected ringing artifactareas, based on the window location information.
 29. The device of claim28, wherein the combiner selects pixels with reduced ringing artifactsfrom the processed pixels in the detected ringing artifact areas,substantially in noisy picture locations.
 30. The device of claim 22wherein the input image comprises a decompressed image.